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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Match Data Pro is a sophisticated tool for managing data quality that aims to integrate, cleanse, analyze, match, eliminate duplicates, and consolidate records from various files, databases, and systems with remarkable efficiency and accuracy. It features cutting-edge AI-enabled fuzzy matching and adjustable rule-based logic to identify duplicates and inconsistencies within extensive datasets, assisting users in correcting errors, standardizing formats, and generating trustworthy golden records without the need for coding expertise. The tool also offers extensive data profiling with essential metrics to identify quality concerns prior to processing, robust data cleansing functionalities for normalizing and standardizing information, along with address verification features that enhance accuracy. Furthermore, Match Data Pro is equipped with Senzing AI entity resolution and customizable matching algorithms to accommodate minor data variations, ensuring high-performance processing capable of scaling up to millions of records. Additionally, it facilitates project job automation through scheduling, reusable rules, and seamless API integrations, making it a comprehensive solution for effective data management.

Description

NORMLZ is a tool designed for data normalization that effectively standardizes and rectifies inconsistent data within HubSpot. This software tackles the difficulties posed by large datasets where differing data formats can obstruct analysis, lead to ineffective campaigns resulting in potential revenue loss, and complicate reporting. It seamlessly integrates with your HubSpot account, and there are plans to extend support to Salesforce and Apollo in the future. The engine proficiently identifies and harmonizes variations, transforming entries like "CEO," "C.E.O," and "Chief Executive Officer" into a unified format. Additionally, it consolidates location information such as "New York," "NYC," and "New York City," while ensuring consistency in company names like "IBM Corp" and "IBM Corporation." With NORMLZ, users can enhance their data quality, leading to more accurate insights and improved decision-making.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

No images available

Integrations

Dropbox Yes 
Dropbox Paper Yes 
Google Chrome Yes 
Google Drive Yes 
HubSpot CRM No 
JSON Yes 
Microsoft OneDrive Yes 
Microsoft Teams Yes 
SQL Yes 
Snowflake Yes 
Zip Yes 

Integrations

Dropbox No 
Dropbox Paper No 
Google Chrome No 
Google Drive No 
HubSpot CRM Yes 
JSON No 
Microsoft OneDrive No 
Microsoft Teams No 
SQL No 
Snowflake No 
Zip No 

Pricing Details

$27 per month
Free Trial Yes 
Free Version No 

Pricing Details

$5/month
Free Trial Yes 
Free Version No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs No 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Match Data Pro

Founded

2023

Country

United States

Website

matchdatapro.com

Vendor Details

Company Name

HubProsper

Founded

2025

Website

normlz.com

Product Features

Data Cleansing

Address/ZIP Code Cleaning No 
Charting No 
Data Consolidation / ETL No 
Data Mapping No 
Multi Data Format Support No 
Phone/Email Validation No 
Raw Data Ingestion No 
Sample Testing No 
Validation / Matching / Reconciliation No 

Data Quality

Address Validation No 
Data Deduplication No 
Data Discovery No 
Data Profililng No 
Master Data Management No 
Match & Merge No 
Metadata Management No 

Product Features

Data Quality

Address Validation No 
Data Deduplication No 
Data Discovery No 
Data Profililng No 
Master Data Management No 
Match & Merge No 
Metadata Management No 

Alternatives

Alternatives

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Data Ladder
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